Seismic exploration uses information in an attempt to determine the character of the ground without actually drilling into the ground. Many seismic exploration systems are based on launching acoustic probe waves with a vibratory element and measuring reflected probe waves from underground layers with an array of detectors distributed on ground surface. An example of such technique is illustrated with reference to FIG. 1.
An acoustic probe wave or seismic wave is initiated at a point on the surface of the ground shown as shock point 100. The acoustic wave essentially emanates from a point at the source point 100. The wavefront would approach a spherical shape and travel outward in all directions if the underground is a homogeneous medium. Various geological formations exist and interact with the acoustic wave. In particular, the acoustic wave is reflected from various layers in the ground. Detection of the spatial and temporal characteristics of the reflections from these underground formations forms the basis for seismography.
The acoustic probe wave can be generated by a blast of dynamite. Alternatively, the probe ware may be generated by using a mechanized vibrator which vibrates the ground at certain frequencies. The vibrator can be controlled by a central control unit (e.g. a computer), for example, to produce a swept frequency signal for improved signal-to-noise ratios.
A plurality of sensors are spatially distributed on or near the ground surface to measure the reflections of the acoustic wave from the layers. Well-known sensors, such as geophones, are normally used to detect the reflected seismic waves. Geophones are miniature force sensors operable to convert vibrations into electrical signals. Geophones are spread over the surface or near the surface of the ground in an array to determine magnitudes of vibrations caused by the reflected acoustic waves. Hundreds or thousands of geophones can be used in an array. A single, or groups of geophones (e.g., geophone station), are attached by cables to a central processing element which receives the geophone data and processes it to extract various information about the structure of the earth from these seismic reflection paths.
FIGS. 2A and 2B show an example to illustrate the basic process. A rectangular area is assumed to be the area of interest on or near the ground surface (FIG. 2A). A line A-A' indicates a survey trace in the east-west direction. Seismic data is taken along line A-A' to extract geological information thereunder. A multiplicity of such east-west survey traces of a predetermined spacing are surveyed and a multiplicity of north-south traces (e.g., line B-B') are also surveyed to obtain a 2D mapping of the geological profile of the earth under survey area. FIG. 2B shows a seismic vertical cross-section with three reflection surfaces Ri, R2, and R3 underneath the line A-A' in the mapping area for illustration purpose.
One way to perform the survey is to initiate acoustic probe waves at successive locations along the line A-A' to obtain sufficient data to represent the geological profile underneath line A-A'. For example, an acoustic wave is sent to the earth at a source point SP1. Arrays of geophones are symmetrically distributed with a predetermined spacing about SP1 along line A-A'. The spatial spread of the geophone array is usually chosen so that a sufficient field of view can be achieved to receive reflections from the deep as well as shallow reflection layers of interest. The spacing or density of the geophone arrays is selected for a desired mapping resolution and full coverage of the survey area. One or more acoustic waves are initiated and the respective reflections from the reflection surfaces Rl, R2, and R3 are measured by the geophone arrays.
A subsequent detection location SP2 along line A-A' should be chosen so that every location between SP1 and SP2 is covered by the acoustic waves from either source point. FIG. 2B shows that SP2 to the east of SP1 should be no further than the location of the outer most geophone in the array on the east side of SP1. Otherwise, reflection surface R1 will not be fully covered.
The processing of the information from these geophones is well-known in the art. Modern trends have attempted to correlate the data from these geophones for various reasons, including to enhance the signal-to-noise ratio. Specifically, a signal received by a geophone due to an acoustic probe wave is correlated with a reference signal with a waveform identical to that of the probe wave using the central processing element. A seismogram can be composed from the correlation signals for each source point and thereby a 2D mapping of the geometric profile of the reflection surfaces underneath the rectangular area can be constructed.
The system and signal processing are complicated by noise. Seismic detections often have signal to noise ratios less than 1, sometimes as low as 0.01. Said another way, there is usually three to 100 times as much noise as signal. The correlation techniques are crucial for extracting desired signals from noise and proper understanding of the data in many detection systems. Sometimes, the correlations may not be done properly or in the best way possible in retrospect. These detections are often carried out multiple times in attempts to average out noise.
One prior-art technique for extracting a weak correlation signal from a noisy background was developed by Continental Oil Company, named "VIBROSEIS". It is similar to the well-known "chirp radar" technique for detecting a radar signal embedded in noise. A sweep signal in a pre-selected frequency range is initiated repeatedly several times at each source point. The signals received by each geophone due to multiple "sweeps" in the same frequency range are summed to form a composite signal. Next, a reference signal with the same frequency chirp as each sweep signal is correlated with the composite signal to produce a correlation signal. This improves the signal-to-noise ratio in the detection.
However, "Vibroseis" produces undesired side lobes near the main correlation peak, which constitute damaging noise on the final processed seismic cross sections. These side lobes are the well-known Klauder wavelets that are caused by the limited frequency bandwidth of the sweep signal. It is known that increasing the bandwidth and/or the time duration of the sweep can reduce the amplitude of the side lobes. Usefulness of such methods of reducing side lobes is essentially eliminated by practical limitations inherent in seismic prospecting. In addition, the process of first summing multiple sweeps and then performing correlation in "Vibroseis" actually amplifies the side lobes since all side lobes are in phase with respect to one another and add constructively.
Martin recognized the problems of the "Vibroseis" technique and developed an improved chirp technique called VARISWEEP.TM.. This is disclosed in U.S. Pat. No. 4,037,190, the content of which is incorporated herewith by reference. The VARISWEEP.TM. technique makes a plurality of passes of vibration with each having a chirp in a different frequency range. The bandwidth of each sweep can be chosen to be approximately within the frequency range to which the earth is most responsive (e.g., from 10 Hz and 100 Hz). The sweeps, for example, might include 10-48 Hz for sweep 1, 12-52 Hz for sweep 2, 14-56 Hz for sweep 3, etc.
In VARISWEEP.TM., each of the multiple different frequency sweeps is correlated with a respective reference signal for that particular sweep. Instead of having only one correlation signal in Vibroseis, there are a multiplicity of correlation signals in VARISWEEP.TM.. Next, all correlation signals from the multiple sweeps are summed to generate one composite correlation signal. Contrast to Vibroseis, the side lobes from different sweep correlation signals are out of phase with respect to one other due to the relative frequency shift, resulting in destructive summation thereof. Thus, the side lobes are substantially minimized in the composite correlation signal in VARISWEEP.TM..
VARISWEEP.TM. has other beneficial features. For example, the multiple frequency ranges of the multiple sweeps can be purposely selected in a way such that some frequency ranges are in a high frequency range well above the frequency range of the ground roll while other sweeps have spectral overlaps with the ground-roll frequency range. Therefore, sweeps with frequencies above ground-roll frequency can be individually correlated and then summed together to generate a first composite correlation signal that is substantially free of ground-roll noise. Meanwhile, all sweeps are used as in conventional VARISWEEP.TM. processing to generate a second composite correlation signal of lower frequency for better resolution of deep reflectors. This can further improve the accuracy in seismic profiling.
For another example, the frequency ranges of the multiple sweeps in VARISWEEP.TM. can include high frequencies for detecting shallow reflectors and low frequencies for detecting deep beds. This is because the earth attenuates high frequency seismic waves faster and at a higher degree of completeness than it does to waves at lower frequencies.
One common limitation in prior-art techniques for seismic prospecting including VARISWEEP.TM. lies in lack of mechanisms to adjust the characteristics of the probe waves for optimizing detection of locations within the mapping area that have anomalies not best resolved by predetermined probe waves. Anomalous results in the past have often been discarded. The inventor of the present invention recognized that anomalies often reveal important seismic information and provide critical evidence in explorations such as oil exploration. Thus, prior art techniques can produce an erroneous profiling in these anomalous locations and lose valuable information.
FIG. 3 shows a seismic cross section across Delaware basin to Central Basin Platform in west Texas near the boundary of New Mexico and Texas. The edge of the Central Basin Platform 302 is somewhat like a cliff, a significant portion of which is very steep, approaching vertical. A fault 304 that is substantially vertical is located to the east of the edge 302. A reef 306 is formed close to the top of the platform edge 302. In addition, a fill zone 308 is also located near the ground surface within a general area 310 having the edge, the fault, and the reef. A person skilled in the art would recognize adverse effects caused by the these geological formations in seismic profiling the area 310. Many prior-art systems based on detection of reflected acoustic waves cannot produce an accurate seismic cross section for regions like 310 due to their incapability in reducing noise caused by these unusual formations including wavefront deformation, scattering, absorption, etc. Region 310 in FIG. 3 may represent an extraordinary collection of irregular formations. However, some of these anomalies and others alike often appear in seismic prospecting.
Another common limitation is that many prior-art systems only have the processed data stored in memory such as data for a final correlation signal from each geophone. Unprocessed raw data representing the signals directly generated by each geophone is not saved and therefore is not available for further analysis and processing. This, however, is not because the prior-art systems cannot implement appropriate means for saving the raw data but rather because the established survey techniques and the seismic survey industry fail to recognize the significance and necessity to save such raw data. The present inventor realized that unprocessed raw data from geophones, if obtained in a proper manner, can be used to provide important and sometimes critical information on the geological structures under survey. Such properly obtained raw data is particularly vital to reveal unusual geological formations as illustrated in region 310 of FIG. 3.
The present inventor further recognized that, for a given geological environment and survey hardware system, various processing techniques and possibilities can be utilized to analyze the properly obtained raw data to achieve a maximized resolution and signal-to-noise ratios that are difficult to obtain with many prior-art techniques.
It is therefore an object of the present invention to obviate these problems and limitations by going beyond the established techniques in the art. More specifically, the present invention teaches a vibratory seismic prospecting system based on a novel method of raw data collection, data storage, and data processing and analysis beyond conventional correlation approaches.
In a preferred embodiment, a plurality of geophone sensing arrays with different spatial spread and density of the geophones and other spatial parameters (e.g. azimuth coordinates) are determined based on prior knowledge or current testing for a given survey area. This, at least in part, constitutes the geometry test in accordance with the present invention. A plurality of test sweeps with predetermined different sweep frequency ranges and optionally different bandwidth are used for each of the geophone configurations in the geometry test to obtain a preliminary correlation results. Different time durations for the test sweeps can be used to further examine the temporal characteristics of the survey area.
Next, results of test sweeps are analyzed from a number of aspects, including frequency domain analysis, spatial domain analysis, and time domain analysis.
Based on analysis of the test sweeps, parameters of multiple data-collection sweeps are determined to optimize the detection of the survey area, including but not limited to, frequency range, sweep bandwidth, time duration of a sweep, amount of energy in a sweep signal, distribution of the source points in the survey area, and spatial configuration of the geophone arrays (e.g., spread, density, and azimuth coordinate). Data-collection sweeps are then initiated and the raw data is collected from the geophones and saved for subsequent analysis and processing. In this way, sweep frequencies can be chosen to best resolve the geologic beds which usually vary widely from the surface downward and also horizontally.
Next, a plurality of data processing techniques are used to analyze the raw data to achieve the maximal resolution and signal-to-noise ratio. Particularly, raw data is processed to further reveal anomalous features in the survey area. Each of the sweeps can be processed individually or can be grouped with other sweeps in any systematic, or weighted manner to achieve a desired result.